Method of soft decision decoding and apparatus for soft decision decoding

Abstract

A soft decision decoding method in a multiple-input multiple-output system which respectively receives two simultaneously transmitted data streams, a first transmitting symbol and a second transmitting symbol, in a first receiving signal and a second receiving signal is provided. The soft decision decoding method includes calculating common metrics corresponding to distances between first candidate symbols, which correspond to combinations of all bits that the first transmitting symbol can have, and the first receiving signal using a channel matrix corresponding to a communication channel through which the first and second transmitting symbols are transmitted and determining intermediate nodes between the second receiving signal and the first candidate symbols and nodes between the second receiving signal and second candidate symbols corresponding to combinations of all bits that the second transmitting symbol can have; selecting first nearest candidate symbols that are at a shortest distance from the intermediate nodes on a signal constellation from among the second candidate symbols and determining a soft decision metric for each bit value of the first transmitting symbol based on the first nearest candidate symbols and the common metrics; and determining second nearest candidate symbols based on a logic value of a predetermined bit of each of the second candidate symbols and the positions of the intermediate nodes on the signal constellation and determining a soft decision metric for each bit value of the second transmitting symbol using the second nearest candidate symbols and the common metrics.

The invention claimed is: 
     
       1. A soft decision decoding method in a multiple-input multiple-output system which respectively receives two simultaneously transmitted data streams, a first transmitting symbol and a second transmitting symbol, in a first receiving signal and a second receiving signal, the soft decision decoding method comprising:
 calculating common metrics corresponding to distances between first candidate symbols, which correspond to combinations of all bits that the first transmitting symbol can have, and the first receiving signal using a channel matrix corresponding to a communication channel through which the first and second transmitting symbols are transmitted and determining intermediate nodes between the second receiving signal and the first candidate symbols and nodes between the second receiving signal and second candidate symbols corresponding to combinations of all bits that the second transmitting symbol can have; 
 selecting first nearest candidate symbols that are at a shortest distance from the intermediate nodes on a signal constellation from among the second candidate symbols and determining a soft decision metric for each bit value of the first transmitting symbol based on the first nearest candidate symbols and the common metrics; and 
 determining second nearest candidate symbols based on a logic value of a pre-determined bit of each of the second candidate symbols and the positions of the intermediate nodes on the signal constellation and determining a soft decision metric for each bit value of the second transmitting symbol using the second nearest candidate symbols and the common metrics. 
 
     
     
       2. The soft decision decoding method of  claim 1 , further comprising the operation of decomposing the channel matrix into a normal matrix and a triangular matrix and converting the first and second receiving signals and the first candidate symbols based on the normal and triangular matrixes before calculating the common metrics and the intermediate nodes. 
     
     
       3. The soft decision decoding method of  claim 2 , wherein the channel matrix is subjected to QR decomposition and is decomposed into the normal matrix and the triangular matrix. 
     
     
       4. The soft decision decoding method of  claim 2 , wherein the common metrics are calculated by
   | z   1   —r   11   s   j   1 | 2    
 where z 1  is an element of a matrix 
 
       
         
           
             
               z 
               = 
               
                 ( 
                 
                   
                     
                       
                         z 
                         0 
                       
                     
                   
                   
                     
                       
                         z 
                         1 
                       
                     
                   
                 
                 ) 
               
             
           
         
         determined by the converted first and second receiving signals, r 11  is an element of the triangular matrix 
       
       
         
           
             
               
                 R 
                 = 
                 
                   ( 
                   
                     
                       
                         
                           r 
                           00 
                         
                       
                       
                         
                           r 
                           01 
                         
                       
                     
                     
                       
                         0 
                       
                       
                         
                           r 
                           11 
                         
                       
                     
                   
                   ) 
                 
               
               , 
             
           
         
         s 1   j  is an element of a matrix 
       
       
         
           
             
               s 
               = 
               
                 ( 
                 
                   
                     
                       
                         s 
                         0 
                         i 
                       
                     
                   
                   
                     
                       
                         s 
                         1 
                         j 
                       
                     
                   
                 
                 ) 
               
             
           
         
         determined based on the first and second candidate symbols, and “i” and “j” are respectively indexes with respect to the first and second symbols. 
       
     
     
       5. The soft decision decoding method of  claim 2 , wherein the intermediate nodes are determined by
     z   0   −r   01   s   j   1    
 where z 0  is an element of a matrix 
 
       
         
           
             
               z 
               = 
               
                 ( 
                 
                   
                     
                       
                         z 
                         0 
                       
                     
                   
                   
                     
                       
                         z 
                         1 
                       
                     
                   
                 
                 ) 
               
             
           
         
         determined by the converted first and second receiving signals, r 01  is an element of the triangular matrix 
       
       
         
           
             
               
                 R 
                 = 
                 
                   ( 
                   
                     
                       
                         
                           r 
                           00 
                         
                       
                       
                         
                           r 
                           01 
                         
                       
                     
                     
                       
                         0 
                       
                       
                         
                           r 
                           11 
                         
                       
                     
                   
                   ) 
                 
               
               , 
             
           
         
         s 1   j  is an element of a matrix 
       
       
         
           
             
               s 
               = 
               
                 ( 
                 
                   
                     
                       
                         s 
                         0 
                         i 
                       
                     
                   
                   
                     
                       
                         s 
                         1 
                         j 
                       
                     
                   
                 
                 ) 
               
             
           
         
         determined based on the first and second candidate symbols, and “i” and “j” are respectively indexes with respect to the first and second symbols. 
       
     
     
       6. The soft decision decoding method of  claim 1 , wherein the operation of selecting the first nearest candidate symbols and determining the soft decision metric for each bit value of the first transmitting symbol comprises:
 selecting the first nearest candidate symbols that are at the shortest distance from the intermediate nodes on the signal constellation from among the second candidate symbols; 
 calculating first shortest metrics by adding the common metrics to metrics corresponding to distances between the first nearest candidate symbols and the intermediate nodes; and 
 selecting the soft decision metric for each bit value of the first transmitting symbol from among the first shortest metrics. 
 
     
     
       7. The soft decision decoding method of  claim 6 , wherein the selecting the first nearest candidate symbols comprises dividing the signal constellation into sections more than the number of the first candidate symbols and selecting as a first nearest candidate symbol a first candidate symbol that is located in the same section as each intermediate node. 
     
     
       8. The soft decision decoding method of  claim 6 , wherein the selecting the soft decision metric for each bit value of the first transmitting symbol from among the first shortest metrics comprises:
 defining a minimum metric among the first shortest metrics as a hard decision metric and defining a first candidate symbol and a second candidate symbol that are used to obtain the hard decision metric as a first hard decision candidate symbol and a second hard decision candidate symbol, respectively; 
 when a logic value of a certain bit of the first transmitting symbol is the same as that of a corresponding bit of the first hard decision candidate symbol, selecting the hard metric as the soft decision metric for the logic value of the certain bit of the first transmitting symbol; and 
 when a logic value of a certain bit of the first transmitting symbol is different from that of a corresponding bit of the first hard decision candidate symbol, selecting metrics connected with second candidate symbols whose bits corresponding to the certain bit have the same logic value as the certain bit of the first transmitting symbol from the first shortest metrics and selecting a minimum of the selected metrics as the soft decision metric for the logic value of the certain bit of the first transmitting symbol. 
 
     
     
       9. The soft decision decoding method of  claim 8 , wherein the operation of selecting the second nearest candidate symbols and determining the soft decision metric for each bit value of the second transmitting symbol comprises:
 when a logic value of a certain bit of the second transmitting symbol is the same as that of a corresponding bit of the second hard decision candidate symbol, selecting the hard metric as the soft decision metric for the logic value of the certain bit of the second transmitting symbol; and 
 when a logic value of a certain bit of the second transmitting symbol is different from that of a corresponding bit of the second hard decision candidate symbol, calculating the soft decision metric for the logic value of the certain bit of the second transmitting symbol using the intermediate nodes, the second candidate symbols, and common metrics. 
 
     
     
       10. The soft decision decoding method of  claim 9 , wherein the calculating the soft decision metric for the logic value of the certain bit of the second transmitting symbol comprises, when the logic value of the certain bit of the second transmitting symbol is different from that of the corresponding bit of the second hard decision candidate symbol:
 (a) selecting candidate symbols whose bits corresponding to the certain bit have the same logic value as the certain bit of the second transmitting symbol from the second candidate symbols; 
 (b) determining candidate symbols, which are at a shortest distance from the intermediate nodes on the signal constellation among the selected second candidate symbols, as the second nearest candidate symbols; 
 (c) calculating second shortest metrics by adding the common metrics to metrics corresponding to distances between the second nearest candidate symbols and the intermediate nodes; and 
 (d) repeating (a) through (c) with respect to each of at least two bit values of the second transmitting symbol and selecting the soft decision metric for the logic value of the certain bit of the second transmitting symbol from second shortest metrics calculated through the repetition of (a) through (c). 
 
     
     
       11. The soft decision decoding method of  claim 10 , wherein information about the second nearest candidate symbols is stored in a look-up table and the soft decision metric for the logic value of the certain bit of the second transmitting symbol is calculated using the information. 
     
     
       12. A soft decision decoding apparatus in a multiple-input multiple-output system which respectively receives two simultaneously transmitted data streams, a first transmitting symbol and a second transmitting symbol, in a first receiving signal and a second receiving signal, the soft decision decoding apparatus comprising:
 a common metric calculation unit configured to calculate common metrics corresponding to distances between first candidate symbols, which correspond to combinations of all bits that the first transmitting symbol can have, and the first receiving signal using a channel matrix corresponding to a communication channel through which the first and second transmitting symbols are transmitted and to determine intermediate nodes between the second receiving signal and the first candidate symbols and nodes between the second receiving signal and second candidate symbols corresponding to combinations of all bits that the second transmitting symbol can have; 
 a first soft decision metric calculation unit configured to select first nearest candidate symbols that are at a shortest distance from the intermediate nodes on a signal constellation from among the second candidate symbols and to determine a soft decision metric for each bit value of the first transmitting symbol based on the first nearest candidate symbols and the common metrics; and 
 a second soft decision metric calculation unit configured to determine second nearest candidate symbols based on a logic value of a predetermined bit of each of the second candidate symbols and the positions of the intermediate nodes on the signal constellation and to determine a soft decision metric for each bit value of the second transmitting symbol using the second nearest candidate symbols and the common metrics.